Using algorithm="plinear" as shown by example below makes
sum-of-exponentials fitting problems better conditioned.
A1 <- 1
A2 <- 2
k1 <- -.5
k2 <- -2
x <- seq(1,10,length=200)
y <- A1*exp(k1*x) + A2*exp(k2*x) + .001*rnorm(200)
aa <- nls(y~cbind(exp(k1*x), exp(k2*x)), algorithm="plinear",
st
Thank you! Now it's working.
Peter Dalgaard schrieb:
Jonas Weickert wrote:
Hi,
I want to do a biexponential Fit, i.e.
y ~ A1*exp(k1*x) + A2*exp(k2*x)
Is this possible? I tried nls() but it stopped with several
(different) errors. I'm using y and x as simple vectors and the
formula for nls(
Jonas Weickert wrote:
Hi,
I want to do a biexponential Fit, i.e.
y ~ A1*exp(k1*x) + A2*exp(k2*x)
Is this possible? I tried nls() but it stopped with several (different)
errors. I'm using y and x as simple vectors and the formula for nls()
exactly as mentioned above.
Yes, it is possible, wi
Hi,
I want to do a biexponential Fit, i.e.
y ~ A1*exp(k1*x) + A2*exp(k2*x)
Is this possible? I tried nls() but it stopped with several (different)
errors. I'm using y and x as simple vectors and the formula for nls()
exactly as mentioned above.
Thanks a lot!
Jonas
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